Research On Algorithms For Isolated Word Recognition And Its Implementation On SOPC

With the rapid development of information technology, especially in computer science, speech recognition has gained the great improvement both in theory and practice. Some of mature techniques have been realized by hardware or several speech recognition chips which are based on integrate circuit or embedded system. Due to the expensive price and the lack of design flexibility, the performance of these chips can't be elevated currently.Based on thorough research on algorithms for isolated word recognition, this thesis makes improvements on the endpoint detection and feature extraction. We adopt zero-energy threshold judgment algorithm in detection. In the feature extraction, the Schur algorithm is used to solve the relevant equation, which is more appropriate for hardware implementation. All these not only increase the computation efficiency but also make the hardware implementation of the algrithms much easier, which has been supported by experiments.At the same time, we implement the whole algorithm of isolated word recognition on FPGA (Field Programmable Gate Array) embedded hardware system based on the concept of SOPC (System on a Programmable Chip). The abstract algorithm described in Matlab has been connected to the detailed hardware design by the tool of DSP Builder. The realization of the module of I2C configuration, module of speech data preprocessing, module of speech data collection and module of speech recognition have totally shown the advantage of NiosⅡsoft-core CPU in FPGA design, such as user-definable function.